Nana Zhang¹, Kun Zhu¹, Shi Ying^{1, *}, Xu Wang²

CMC-Computers, Materials & Continua, Vol.65, No.1, pp. 279-308, 2020, DOI:10.32604/cmc.2020.011001 - 23 July 2020

Abstract Software defect prediction plays an important role in software quality assurance. However, the performance of the prediction model is susceptible to the irrelevant and redundant features. In addition, previous studies mostly regard software defect prediction as a single objective optimization problem, and multi-objective software defect prediction has not been thoroughly investigated. For the above two reasons, we propose the following solutions in this paper: (1) we leverage an advanced deep neural network—Stacked Contractive AutoEncoder (SCAE) to extract the robust deep semantic features from the original defect features, which has stronger discrimination capacity for different classes… More >

Shu Fang¹, Lei Huang¹, Yi Wan², Weize Sun^{1, *}, Jingxin Xu³

CMC-Computers, Materials & Continua, Vol.64, No.1, pp. 541-555, 2020, DOI:10.32604/cmc.2020.010066 - 20 May 2020

Abstract With the development of science and technology, the status of the water environment has received more and more attention. In this paper, we propose a deep learning model, named a Joint Auto-Encoder network, to solve the problem of outlier detection in water supply data. The Joint Auto-Encoder network first expands the size of training data and extracts the useful features from the input data, and then reconstructs the input data effectively into an output. The outliers are detected based on the network’s reconstruction errors, with a larger reconstruction error indicating a higher rate to be… More >

Chao Luo¹, Canghong Shi¹, Xiaojie Li^{1, *}, Xin Wang⁴, Yucheng Chen³, Dongrui Gao¹, Youbing Yin⁴, Qi Song⁴, Xi Wu¹, Jiliu Zhou¹

CMC-Computers, Materials & Continua, Vol.63, No.2, pp. 995-1012, 2020, DOI:10.32604/cmc.2020.07968 - 01 May 2020

Abstract Myocardial segmentation and classification play a major role in the diagnosis of cardiovascular disease. Dilated Cardiomyopathy (DCM) is a kind of common chronic and life-threatening cardiopathy. Early diagnostics significantly increases the chances of correct treatment and survival. However, accurate and rapid diagnosis of DCM is still challenge due to high variability of cardiac structure, low contrast cardiac magnetic resonance (CMR) images, and intrinsic noise in synthetic CMR images caused by motion artifact and cardiac dynamics. Moreover, visual assessment and empirical evaluation are widely used in routine clinical diagnosis, but they are subject to high inter-observer… More >

Xiangmao Chang^{1, 2, *}, Yuan Qiu¹, Shangting Su¹, Deliang Yang³

CMC-Computers, Materials & Continua, Vol.63, No.2, pp. 691-703, 2020, DOI:10.32604/cmc.2020.07923 - 01 May 2020

Abstract Wireless sensor networks are increasingly used in sensitive event monitoring. However, various abnormal data generated by sensors greatly decrease the accuracy of the event detection. Although many methods have been proposed to deal with the abnormal data, they generally detect and/or repair all abnormal data without further differentiate. Actually, besides the abnormal data caused by events, it is well known that sensor nodes prone to generate abnormal data due to factors such as sensor hardware drawbacks and random effects of external sources. Dealing with all abnormal data without differentiate will result in false detection or More >

Chaochao Luo¹, Shen Su^{2, *}, Yanbin Sun², Qingji Tan³, Meng Han⁴, Zhihong Tian^{2, *}

CMC-Computers, Materials & Continua, Vol.62, No.1, pp. 399-411, 2020, DOI:10.32604/cmc.2020.06507

Abstract Since the web service is essential in daily lives, cyber security becomes more and more important in this digital world. Malicious Uniform Resource Locator (URL) is a common and serious threat to cybersecurity. It hosts unsolicited content and lure unsuspecting users to become victim of scams, such as theft of private information, monetary loss, and malware installation. Thus, it is imperative to detect such threats. However, traditional approaches for malicious URLs detection that based on the blacklists are easy to be bypassed and lack the ability to detect newly generated malicious URLs. In this paper, More >

Cong Xu^{1, 2}, Zhenqi Sun^{2, 3}, Qi Jia^{2, 3}, Dezheng Zhang^{2, 3}, Yonghong Xie^{2, 3,*}, Alan Yang⁴

CMC-Computers, Materials & Continua, Vol.62, No.1, pp. 113-122, 2020, DOI:10.32604/cmc.2020.05239

Abstract With the success of new speech-based human-computer interfaces, there is a great need for effective and friendly dialogue agents that can communicate with people naturally and continuously. However, the lack of personality and consistency is one of critical problems in neural dialogue systems. In this paper, we aim to generate consistent response with fixed profile and background information for building a realistic dialogue system. Based on the encoder-decoder model, we propose a retrieval mechanism to deliver natural and fluent response with proper information from a profile database. Moreover, in order to improve the efficiency of More >

Chaoyang Xia¹, Jing Peng¹, Zongqing Ma², Xiaojie Li^1,*

Journal of Information Hiding and Privacy Protection, Vol.1, No.3, pp. 109-117, 2019, DOI:10.32604/jihpp.2019.07198

Abstract Cardiomyopathy is one of the most serious public health threats. The precise structural and functional cardiac measurement is an essential step for clinical diagnosis and follow-up treatment planning. Cardiologists are often required to draw endocardial and epicardial contours of the left ventricle (LV) manually in routine clinical diagnosis or treatment planning period. This task is time-consuming and error-prone. Therefore, it is necessary to develop a fully automated end-to-end semantic segmentation method on cardiac magnetic resonance (CMR) imaging datasets. However, due to the low image quality and the deformation caused by heartbeat, there is no effective… More >

Yanzhen Wang¹, Xuefeng Yan^1,*

CMES-Computer Modeling in Engineering & Sciences, Vol.121, No.1, pp. 123-144, 2019, DOI:10.32604/cmes.2019.07052

Abstract A single model cannot satisfy the high-precision prediction requirements given the high nonlinearity between variables. By contrast, ensemble models can effectively solve this problem. Three key factors for improving the accuracy of ensemble models are namely the high accuracy of a submodel, the diversity between subsample sets and the optimal ensemble method. This study presents an improved ensemble modeling method to improve the prediction precision and generalization capability of the model. Our proposed method first uses a bagging algorithm to generate multiple subsample sets. Second, an indicator vector is defined to describe these subsample sets. More >

Kehua Yang^1,*, Yaodong Wang¹, Wei Zhang¹, Jiqing Yao², Yuquan Le¹

CMC-Computers, Materials & Continua, Vol.61, No.2, pp. 569-581, 2019, DOI:10.32604/cmc.2019.05952

Abstract Keyphrase greatly provides summarized and valuable information. This information can help us not only understand text semantics, but also organize and retrieve text content effectively. The task of automatically generating it has received considerable attention in recent decades. From the previous studies, we can see many workable solutions for obtaining keyphrases. One method is to divide the content to be summarized into multiple blocks of text, then we rank and select the most important content. The disadvantage of this method is that it cannot identify keyphrase that does not include in the text, let alone… More >

Syed Falahuddin Quadri¹, Xiaoyu Li^1,*, Desheng Zheng², Muhammad Umar Aftab¹, Yiming Huang³

Journal on Big Data, Vol.1, No.1, pp. 1-7, 2019, DOI:10.32604/jbd.2019.05899

Abstract Given the glut of information on the web, it is crucially important to have a system, which will parse the information appropriately and recommend users with relevant information, this class of systems is known as Recommendation Systems (RS)-it is one of the most extensively used systems on the web today. Recently, Deep Learning (DL) models are being used to generate recommendations, as it has shown state-of-the-art (SoTA) results in the field of Speech Recognition and Computer Vision in the last decade. However, the RS is a much harder problem, as the central variable in the… More >